10559560
8323
Heinrich Peters
14954
Supervised Classification
18298
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC)(4)
8276172
copy
true
17405
with_mean
true
17405
with_std
true
17405
add_indicator
false
17407
copy
true
17407
fill_value
null
17407
missing_values
NaN
17407
strategy
"most_frequent"
17407
verbose
0
17407
categorical_features
null
17408
categories
null
17408
drop
null
17408
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
17408
handle_unknown
"ignore"
17408
n_values
null
17408
sparse
true
17408
C
1.0167588209539864
17495
cache_size
200
17495
class_weight
null
17495
coef0
-0.6354734369237474
17495
decision_function_shape
"ovr"
17495
degree
3
17495
gamma
0.0003345572257968965
17495
kernel
"poly"
17495
max_iter
-1
17495
probability
true
17495
random_state
1
17495
shrinking
true
17495
tol
0.001
17495
verbose
false
17495
memory
null
18298
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
18298
verbose
false
18298
n_jobs
null
18299
remainder
"drop"
18299
sparse_threshold
0.3
18299
transformer_weights
null
18299
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "num", "step_name": "num", "argument_1": [false, true, false, false, false, false, false, false, false, false, false, false, false, false, true, false, false, false, true, true, false, true, true, true, true, true, true, true, true, true, true, true, true, true, false, true, false]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [true, false, true, true, true, true, true, true, true, true, true, true, true, true, false, true, true, true, false, false, true, false, false, false, false, false, false, false, false, false, false, false, false, false, true, false, true]}}]
18299
verbose
false
18299
memory
null
18300
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
18300
verbose
false
18300
memory
null
18301
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
18301
verbose
false
18301
openml-python
Sklearn_0.21.2.
6332
cylinder-bands
https://www.openml.org/data/download/1854224/phpAz9Len
-1
22044107
description
https://api.openml.org/data/download/22044107/description.xml
-1
22044108
predictions
https://api.openml.org/data/download/22044108/predictions.arff
area_under_roc_curve
0.7700461088618983 [0.770046,0.770046]
average_cost
0
f_measure
0.7149789928093471 [0.663755,0.752412]
kappa
0.41617523167649534
kb_relative_information_score
0.22565377906005185
mean_absolute_error
0.3902979092172828
mean_prior_absolute_error
0.48794587945879536
weighted_recall
0.7148148148148148 [0.666667,0.75]
number_of_instances
540 [228,312]
precision
0.7151628486831854 [0.66087,0.754839]
predictive_accuracy
0.7148148148148148
prior_entropy
0.9824743303740947
relative_absolute_error
0.7998795064120252
root_mean_prior_squared_error
0.49391365607219145
root_mean_squared_error
0.4373114231753799
root_relative_squared_error
0.8854005508838605
total_cost
0
unweighted_recall
0.7083333333333333 [0.666667,0.75]
area_under_roc_curve
0.8316970546984572 [0.831697,0.831697]
area_under_roc_curve
0.7980364656381488 [0.798036,0.798036]
area_under_roc_curve
0.8134642356241234 [0.813464,0.813464]
area_under_roc_curve
0.6921458625525948 [0.692146,0.692146]
area_under_roc_curve
0.7741935483870968 [0.774194,0.774194]
area_under_roc_curve
0.6690042075736327 [0.669004,0.669004]
area_under_roc_curve
0.9158485273492287 [0.915849,0.915849]
area_under_roc_curve
0.6423562412342216 [0.642356,0.642356]
area_under_roc_curve
0.8352272727272727 [0.835227,0.835227]
area_under_roc_curve
0.7457386363636362 [0.745739,0.745739]
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
f_measure
0.7761994949494949 [0.727273,0.8125]
f_measure
0.7388994107744108 [0.681818,0.78125]
f_measure
0.705338441890166 [0.68,0.724138]
f_measure
0.6666666666666666 [0.608696,0.709677]
f_measure
0.7388994107744108 [0.681818,0.78125]
f_measure
0.5751140048314796 [0.510638,0.622951]
f_measure
0.8337402627601441 [0.808511,0.852459]
f_measure
0.6470311581422692 [0.577778,0.698413]
f_measure
0.7242568693562764 [0.680851,0.754098]
f_measure
0.7407407407407407 [0.681818,0.78125]
kappa
0.5404255319148936
kappa
0.46382978723404245
kappa
0.40740740740740744
kappa
0.3183730715287517
kappa
0.46382978723404245
kappa
0.13389121338912138
kappa
0.6610878661087867
kappa
0.27644569816643155
kappa
0.4367176634214186
kappa
0.4630681818181817
kb_relative_information_score
0.330596168361911
kb_relative_information_score
0.27434325243279356
kb_relative_information_score
0.28510210587128204
kb_relative_information_score
0.13281555598228958
kb_relative_information_score
0.2329273641732145
kb_relative_information_score
0.13392750465150105
kb_relative_information_score
0.33892056111741814
kb_relative_information_score
0.10533179912240068
kb_relative_information_score
0.25701569900825905
kb_relative_information_score
0.16531194523325052
mean_absolute_error
0.34202054700715767
mean_absolute_error
0.36890140172676233
mean_absolute_error
0.36059827051511123
mean_absolute_error
0.4303830140460883
mean_absolute_error
0.3903129223856458
mean_absolute_error
0.4273555292964495
mean_absolute_error
0.34684056748935965
mean_absolute_error
0.44386448341508344
mean_absolute_error
0.3746580356359214
mean_absolute_error
0.41804432065524755
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.4856498564985656
mean_prior_absolute_error
0.4856498564985656
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [22,32]
number_of_instances
54 [22,32]
precision
0.7768157768157766 [0.761905,0.787879]
precision
0.7391374058040725 [0.714286,0.757576]
precision
0.7146776406035665 [0.62963,0.777778]
precision
0.6666666666666666 [0.608696,0.709677]
precision
0.7391374058040725 [0.714286,0.757576]
precision
0.5765432098765432 [0.5,0.633333]
precision
0.8347222222222223 [0.791667,0.866667]
precision
0.6463594276094277 [0.590909,0.6875]
precision
0.730727969348659 [0.64,0.793103]
precision
0.7407407407407407 [0.681818,0.78125]
predictive_accuracy
0.7777777777777777
predictive_accuracy
0.7407407407407408
predictive_accuracy
0.7037037037037037
predictive_accuracy
0.6666666666666667
predictive_accuracy
0.7407407407407408
predictive_accuracy
0.5740740740740741
predictive_accuracy
0.8333333333333333
predictive_accuracy
0.6481481481481481
predictive_accuracy
0.7222222222222223
predictive_accuracy
0.7407407407407408
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9757955887617137
prior_entropy
0.9757955887617137
relative_absolute_error
0.7001159161984528
relative_absolute_error
0.7551410145292254
relative_absolute_error
0.7381445084232943
relative_absolute_error
0.8809938491467965
relative_absolute_error
0.7989703883328484
relative_absolute_error
0.8747965891347367
relative_absolute_error
0.7099824961028511
relative_absolute_error
0.9085904112877776
relative_absolute_error
0.7714571117906384
relative_absolute_error
0.8607936665919353
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.4915838450298872
root_mean_prior_squared_error
0.4915838450298872
root_mean_squared_error
0.40275821201830736
root_mean_squared_error
0.42162783750582783
root_mean_squared_error
0.42247010543060537
root_mean_squared_error
0.46750564051374366
root_mean_squared_error
0.43402865264672197
root_mean_squared_error
0.475612025298374
root_mean_squared_error
0.3740594609468461
root_mean_squared_error
0.49585345292003397
root_mean_squared_error
0.41201758684907047
root_mean_squared_error
0.45304392159897355
root_relative_squared_error
0.8144848903335722
root_relative_squared_error
0.8526443229341422
root_relative_squared_error
0.8543476140846967
root_relative_squared_error
0.9454215183745397
root_relative_squared_error
0.877722089839163
root_relative_squared_error
0.9618147978292894
root_relative_squared_error
0.756448335344379
root_relative_squared_error
1.002748381465005
root_relative_squared_error
0.838143057414795
root_relative_squared_error
0.9216005085997679
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
unweighted_recall
0.7671809256661992 [0.695652,0.83871]
unweighted_recall
0.729312762973352 [0.652174,0.806452]
unweighted_recall
0.7082748948106592 [0.73913,0.677419]
unweighted_recall
0.6591865357643759 [0.608696,0.709677]
unweighted_recall
0.729312762973352 [0.652174,0.806452]
unweighted_recall
0.5673211781206171 [0.521739,0.612903]
unweighted_recall
0.832398316970547 [0.826087,0.83871]
unweighted_recall
0.6374474053295933 [0.565217,0.709677]
unweighted_recall
0.7230113636363636 [0.727273,0.71875]
unweighted_recall
0.7315340909090908 [0.681818,0.78125]
usercpu_time_millis
214.6819999999252
usercpu_time_millis
220.82000000000335
usercpu_time_millis
212.20800000003237
usercpu_time_millis
212.43999999995822
usercpu_time_millis
212.87600000005114
usercpu_time_millis
222.71200000000135
usercpu_time_millis
213.69999999996026
usercpu_time_millis
216.63800000004585
usercpu_time_millis
215.22999999996273
usercpu_time_millis
214.38200000000052
usercpu_time_millis_testing
9.577999999976328
usercpu_time_millis_testing
9.808000000020911
usercpu_time_millis_testing
9.536000000025524
usercpu_time_millis_testing
10.761999999999716
usercpu_time_millis_testing
9.490000000027976
usercpu_time_millis_testing
9.367999999994936
usercpu_time_millis_testing
9.68199999999797
usercpu_time_millis_testing
9.606000000019321
usercpu_time_millis_testing
9.493999999961034
usercpu_time_millis_testing
9.713999999974021
usercpu_time_millis_training
205.10399999994888
usercpu_time_millis_training
211.01199999998244
usercpu_time_millis_training
202.67200000000685
usercpu_time_millis_training
201.6779999999585
usercpu_time_millis_training
203.38600000002316
usercpu_time_millis_training
213.34400000000642
usercpu_time_millis_training
204.01799999996229
usercpu_time_millis_training
207.03200000002653
usercpu_time_millis_training
205.7360000000017
usercpu_time_millis_training
204.6680000000265
wall_clock_time_millis
107.84721374511719
wall_clock_time_millis
110.58497428894043
wall_clock_time_millis
106.27007484436035
wall_clock_time_millis
106.35614395141602
wall_clock_time_millis
106.66203498840332
wall_clock_time_millis
112.3819351196289
wall_clock_time_millis
107.38277435302734
wall_clock_time_millis
108.8097095489502
wall_clock_time_millis
107.90300369262695
wall_clock_time_millis
108.03890228271484
wall_clock_time_millis_testing
4.798173904418945
wall_clock_time_millis_testing
4.910945892333984
wall_clock_time_millis_testing
4.778861999511719
wall_clock_time_millis_testing
5.404949188232422
wall_clock_time_millis_testing
4.748106002807617
wall_clock_time_millis_testing
4.687070846557617
wall_clock_time_millis_testing
4.848718643188477
wall_clock_time_millis_testing
4.834890365600586
wall_clock_time_millis_testing
4.775047302246094
wall_clock_time_millis_testing
4.868745803833008
wall_clock_time_millis_training
103.04903984069824
wall_clock_time_millis_training
105.67402839660645
wall_clock_time_millis_training
101.49121284484863
wall_clock_time_millis_training
100.9511947631836
wall_clock_time_millis_training
101.9139289855957
wall_clock_time_millis_training
107.69486427307129
wall_clock_time_millis_training
102.53405570983887
wall_clock_time_millis_training
103.97481918334961
wall_clock_time_millis_training
103.12795639038086
wall_clock_time_millis_training
103.17015647888184
weighted_recall
0.7777777777777778 [0.695652,0.83871]
weighted_recall
0.7407407407407407 [0.652174,0.806452]
weighted_recall
0.7037037037037037 [0.73913,0.677419]
weighted_recall
0.6666666666666666 [0.608696,0.709677]
weighted_recall
0.7407407407407407 [0.652174,0.806452]
weighted_recall
0.5740740740740741 [0.521739,0.612903]
weighted_recall
0.8333333333333334 [0.826087,0.83871]
weighted_recall
0.6481481481481481 [0.565217,0.709677]
weighted_recall
0.7222222222222222 [0.727273,0.71875]
weighted_recall
0.7407407407407407 [0.681818,0.78125]